code: def setup_class(cls):
      G1 = nx.Graph()
      G1.add_edge(1, 2, weight=10)
      G1.add_edge(2, 3, weight=10)
      G1.add_edge(3, 4, weight=10)
      G1.add_edge(4, 5, weight=10)
      G1.add_edge(5, 6, weight=10)
      G1.add_edge(2, 7, weight=1)
      G1.add_edge(7, 5, weight=1)
  
      G2 = nx.Graph()
      G2.add_edge(0, 5, weight=6)
      G2.add_edge(1, 2, weight=2)
      G2.add_edge(1, 5, weight=3)
      G2.add_edge(2, 4, weight=4)
      G2.add_edge(3, 5, weight=5)
      G2.add_edge(4, 5, weight=1)
  
      G3 = nx.Graph()
      G3.add_edge(1, 2, weight=8)
      G3.add_edge(1, 9, weight=3)
      G3.add_edge(1, 8, weight=6)
      G3.add_edge(1, 10, weight=2)
      G3.add_edge(1, 14, weight=3)
      G3.add_edge(2, 3, weight=6)
      G3.add_edge(3, 4, weight=3)
      G3.add_edge(3, 10, weight=2)
      G3.add_edge(3, 11, weight=1)
      G3.add_edge(4, 5, weight=1)
      G3.add_edge(4, 11, weight=1)
      G3.add_edge(5, 6, weight=4)
      G3.add_edge(5, 11, weight=2)
      G3.add_edge(5, 12, weight=1)
      G3.add_edge(5, 13, weight=3)
      G3.add_edge(6, 7, weight=2)
      G3.add_edge(6, 12, weight=3)
      G3.add_edge(6, 13, weight=1)
      G3.add_edge(7, 8, weight=3)
      G3.add_edge(7, 9, weight=3)
      G3.add_edge(7, 11, weight=5)
      G3.add_edge(7, 13, weight=2)
      G3.add_edge(7, 14, weight=4)
      G3.add_edge(8, 9, weight=2)
      G3.add_edge(9, 14, weight=1)
      G3.add_edge(10, 11, weight=2)
      G3.add_edge(10, 14, weight=1)
      G3.add_edge(11, 12, weight=1)
      G3.add_edge(11, 14, weight=7)
      G3.add_edge(12, 14, weight=3)
      G3.add_edge(12, 15, weight=1)
      G3.add_edge(13, 14, weight=4)
      G3.add_edge(13, 15, weight=1)
      G3.add_edge(14, 15, weight=2)
  
      cls.G1 = G1
      cls.G2 = G2
      cls.G3 = G3
      cls.G1_term_nodes = [1, 2, 3, 4, 5]
      cls.G2_term_nodes = [0, 2, 3]
      cls.G3_term_nodes = [1, 3, 5, 6, 8, 10, 11, 12, 13]
  
      cls.methods = ["kou", "mehlhorn"]
  
file_path: networkx/networkx/algorithms/approximation/tests/test_steinertree.py
imports: import pytest
  import networkx
  from networkx.algorithms.approximation.steinertree import metric_closure, steiner_tree
  from networkx.utils import edges_equal
label_desc: Use image node_id 1 for calling the TestSteinerTree obj's underlying member method code with example usage: obj.setup_class(cls) without return types